2013

Hapfelmeier, Alexander and Ulm, Kurt (2013): Variable selection with Random Forests for missing data. Department of Statistics: Technical Reports, No.137

Jelizarow, Monika and Cieza, Alarcos and Mansmann, Ulrich (2013): Global tests for multivariate ordinal data: on test statistics and when (not) to permute. Department of Statistics: Technical Reports, No.142

Unkel, Steffen and Gower, John C. and Trendafilov, Nickolay T. (2013): On the Procrustean analogue of individual differences scaling (INDSCAL). Department of Statistics: Technical Reports, No.144

2012

Heinzl, Felix and Tutz, Gerhard (2012): Clustering in linear mixed models with a group fused lasso penalty. Department of Statistics: Technical Reports, No.123

Scheipl, Fabian and Greven, Sonja (2012): Identifiability in penalized function-on-function regression models. Department of Statistics: Technical Reports, No.125

Tutz, Gerhard and Pößnecker, Wolfgang and Uhlmann, Lorenz (2012): Variable Selection in General Multinomial Logit Models. Department of Statistics: Technical Reports, No.126

Walter, Gero (2012): A Technical Note on the Dirichlet-Multinomial Model. The Dirichlet Distribution as the Canonically Constructed Conjugate Prior. Department of Statistics: Technical Reports, No.131

2011

Schlicht, Ekkehart (2011): Mend-A Mathematica package for mending time series with missing observations and structural breaks.

2010

Gertheiss, Jan and Tutz, Gerhard (2010): Regularization and Model Selection with Categorial Effect Modifiers. Department of Statistics: Technical Reports, No.73

Herberich, Esther and Sikorski, Johannes and Hothorn, Torsten (2010): A robust procedure for comparing multiple means under heteroscedasticity in unbalanced designs. In: PloS one, Vol. 5, No. 3: e9788

2009

Hofner, Benjamin and Hothorn, Torsten and Kneib, Thomas and Schmid, Matthias (2009): A Framework for Unbiased Model Selection Based on Boosting. Department of Statistics: Technical Reports, No.72

Scharl, Theresa and Grün, Bettina and Leisch, Friedrich (2009): Mixtures of Regression Models for Time-Course Gene Expression Data: Evaluation of Initialization and Random Effects. Department of Statistics: Technical Reports, No.71

Scharl, Theresa and Voglhuber, Ingo and Leisch, Friedrich (2009): Exploratory and Inferential Analysis of Gene Cluster Neighborhood Graphs. Department of Statistics: Technical Reports, No.70

2001

Biller, Clemens and Fahrmeir, Ludwig (2001): Bayesian varying-coefficient models using adaptive regression splines. In: Statistical Modelling, Vol. 1, No. 3: pp. 195-211